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Abstract

Recent positive clinical results in cancer immunotherapy point to the potential of
immune-based strategies to provide effective treatment of a variety of cancers. In
some patients, the responses to cancer immunotherapy are durable, dramatically extending
survival. Extensive research efforts are being made to identify and validate biomarkers
that can help identify subsets of cancer patients that will benefit most from these
novel immunotherapies. In addition to the clear advantage of such predictive biomarkers,
immune biomarkers are playing an important role in the development, clinical evaluation
and monitoring of cancer immunotherapies. This Cancer Immunotherapy Resource Document,
prepared by the Society for Immunotherapy of Cancer (SITC, formerly the International
Society for Biological Therapy of Cancer, iSBTc), provides key references and online
resources relevant to the discovery, evaluation and clinical application of immune
biomarkers. These key resources were identified by experts in the field who are actively
pursuing research in biomarker identification and validation. This organized collection
of the most useful references, online resources and tools serves as a compass to guide
discovery of biomarkers essential to advancing novel cancer immunotherapies.

Introduction

Immunotherapy has emerged as an important treatment strategy for patients with cancer.
With several recent approvals by the U.S. Food and Drug Administration (FDA), cancer
immunotherapy has become the latest addition to the toolbox of effective cancer treatments
that includes chemotherapy, signal transduction inhibitors, anti-angiogenic agents,
radiotherapy, and surgery.

Successful development and testing, regulatory approval and clinical application of
cancer immunotherapies require the identification and validation of biomarkers of
efficacy. The importance of reliable biomarkers to guide immune-based and personalized
cancer therapies is clear. Biomarkers can aid in early disease diagnosis, help clinicians
identify patients most likely to benefit from these expensive treatments, and facilitate
drug discovery, development and biological/clinical evaluation of cancer immunotherapies.

For over twenty-five years the Society for Immunotherapy of Cancer (SITC; formerly
the International Society for Biological Therapy of Cancer, iSBTc) has advanced the
science, development and application of biological therapy/immunotherapy of cancer.
The society has long recognized the importance of biomarkers for cancer immunotherapy,
which has been the focus of a number of SITC/iSBTc symposia and workshops [1-5], and has published recommendations [6] and summaries [7-10].

To support the efforts of investigators involved in research to identify and validate
biomarkers for cancer immunotherapy, the authors and members of the SITC Biomarkers
Taskforce have identified key biomarker references and online resources and organized
these into this SITC/iSBTc Cancer Immunotherapy Biomarkers Resource Document. This
document provides an overview of suggested publications and resources for studies
on biomarkers for cancer immunotherapy. This resource document is divided into two
sections: Part I: Immunotherapy Biomarker References; and Part II: High Throughput
and New Technologies for Biomarker Discovery: Arrays, Platforms, Tools for The Bench
and Online Resources. While many important references and resources in the field are
included in this document, it does not intend to represent an exhaustive list of all
relevant publications, products or resources in the growing, and important field of
immune biomarkers. A comprehensive list of online tools for bioinformatics and molecular
biology research is available from the Bioinformatics Links Directory [11,12].

A draft of the present document was originally provided to attendees of the SITC/iSBTc
Symposium on Immuno-Oncology Biomarkers, 2010 and Beyond: Perspectives from the iSBTc
Biomarker Task Force [1], which was held September 30, 2010 at the National Institutes of Health in conjunction
with the society's 25th Annual Meeting. Following the symposium, the draft document
was posted on the society's website for open comment. The comments were reviewed by
the authors and incorporated into this manuscript. The references and online resources
are organized as outlined in Table 1.

Next generation genome-wide association studies. The Omni family of microarrays will
soon allow researchers to assay up to 5 million markers per sample, including comprehensive
coverage of both common and rare variants identified by 1000 Genomes Project. As novel
SNP sets are released into the public database, researchers using Omni products will
have exclusive access to supplemental arrays that build up to the full 5 million variants

The Fluidigm Dynamic Arrays allow you to use your existing TaqMan® SNP Genotyping assays in a flexible and cost effective fashion. Each dynamic array
allows you to setup up to 9,216 individual TaqMan reactions in a single experiment

Includes over 4.5 million SNP assays, including 3.5 million HapMap, and ~70,000 coding
SNP assays. This collection now includes ~160,000 validated assays with associated
minor allele frequency data available

C. Chromatin Immunoprecipitation (ChIP) Arrays (ChIP on chip)

[ChIP-on-chip (chromatin immunoprecipitation-on-chip), also known as Location Analysis
(LA), is a high throughput (genome-wide) identification and analysis of DNA fragments
that are bound by specific proteins such as histones, transcriptional factors and
polymerases]

Whole genome microarray. The SurePrint G3 Human GE 8 × 60 K Microarrays and Human
GE 4 × 44 K v2 Microarrays are based on updated transcriptome databases for mRNA targets,
while the SurePrint G3 arrays also include probes for lincRNAs (long intergenic non-coding
RNAs). With the combination of mRNA and lincRNAs, it is possible to perform two experiments
on a single microarray, confidently predicting lincRNA function

The HumanHT-12 v4 Expression BeadChip provides high throughput processing of 12 samples
per BeadChip. Each array on the HumanHT-12 v4 Expression BeadChip targets more than
31,000 annotated genes with more than 47,000 probes

The Fluidigm Dynamic Array enables you to test up to 96 individual cells against 96
genes in a single experiment. The dynamic array assembles the cDNA material from individual
cells and reagents to create individual qPCR reactions

Comment: The nCounter Analysis System utilizes a novel digital technology that is based on
direct multiplexed measurement of gene expression and offers high levels of precision
and sensitivity (< 1 copy per cell). The technology uses molecular "barcodes" and
single molecule imaging to detect and count hundreds of unique transcripts in a single
reaction.

Characterization of proteins in extremely small and precious samples. Unlike traditional
protein analysis techniques which require thousands to millions of cells, these assays
require as few as 25 cells per assay

This assay is based on the use of gold nanoparticle probes combined with dynamic light
scattering (DLS) technique, named nanoDLSAY, a highly sensitive, fast and convenient
one-step homogeneous immunoassay for monitoring and detecting biotargets, including
cancer biomarkers

Gene expression analysis software package that includes visualization tools to help
analyze microarray data, including Venn diagrams, a scatter plot, heat maps and line
graphs for clustering, and a gene ontology tree

B. Next Generation Sequencing Data Analysis

Blog

Name:

SEQanswers

Comment:

SEQanswers is a blog founded to be an information resource and user-driven community
focused on all aspects of next-generation genomics. A reasonably thorough table of
next-gen-seq software available in the commercial and public domain is provided

Cufflinks assembles transcripts, estimates their abundances, and tests for differential
expression and regulation in RNA-Seq samples. It accepts aligned RNA-Seq reads and
assembles the alignments into a parsimonious set of transcripts, free of charge

Bowtie is an ultrafast, memory-efficient short read aligner. It aligns short DNA sequences
(reads) to the human genome at a rate of over 25 million 35-bp reads per hour. Bowtie
indexes the genome with a Burrows-Wheeler index to keep its memory footprint small:
typically about 2.2 GB for the human genome (2.9 GB for paired-end).

TopHat is a program that aligns RNA-Seq reads to a genome in order to identify exon-exon
splice junctions. It is built on the ultrafast short read mapping program Bowtie.
TopHat runs on Linux and OS X.

C. Multicolor Cytometric Data-Analysis

Examples

Name:

FlowJo

Comment:

FlowJo is designed around the structure of flow data and the researcher's experiments.
Through FlowJo's patent-pending Groups structure, for example, gates can be applied
to many samples as easily as one

Load FCS files from instruments and do FACS data analysis with a full set of region
tools and gates. The algorithms allow for rapid generation of registers with frequencies/numbers
of all possible suphenotype combinations. Can be used to input data for cluster analysis
and heat maps, allowing rapid visualization of numerous complex data sets.

GemStone is software for analysis of high-dimensional, flow cytometry data. Based
on patented Probability State Modeling technology, GemStone eliminates some problems
that have faced flow cytometry. Subjective gating and associated errors are eliminated.
Population overlaps in multidimensional data are accounted for. Multiple samples may
be combined into one coherent analysis

Gene Set Enrichment Analysis (GSEA) is a computational method that determines whether
an a priori defined set of genes shows statistically significant, concordant differences
between two biological states (e.g., phenotypes)

A tool for biological interpretation of 'omic' data - including data from gene expression
microarrays. Omic experiments often generate lists of dozens or hundreds of genes
that differ in expression between samples

Set of tools that enables the user to translate between disparate ids for the same
gene. It uses data from the UCSC, LocusLink, Unigene, OMIM, Affymetrix and Jackson
data sources to determine how different ids relate. Supported id types include, gene
symbols and names, IMAGE and FISH clones, GenBank accession numbers and UniGene cluster
ids

Panther is a resource that classifies genes by their functions, using published scientific
experimental evidence and evolutionary relationships to predict function even in the
absence of direct experimental evidence. Proteins are also classified

The Cancer Genome Atlas (TCGA) Data Portal provides a platform for researchers to
search, download, and analyze data sets generated by TCGA. Launched in 2006 as a partnership
between the National Cancer Institute and the National Human Genome Research Institute,
both NIH components, The Cancer Genome Atlas (TCGA) has developed a comprehensive
strategy for comparing the genome of cancer cells to the genome of normal cells from
the same patient

The Human Protein Atlas portal is a publicly available database with millions of high-resolution
images showing the spatial distribution of proteins in 46 different normal human tissues
and 20 different cancer types, as well as 47 different human cell lines. The data
is released together with application-specific validation performed for each antibody.
The database was developed in a gene-centric manner with the inclusion of all human
genes predicted from genome efforts

MINT focuses on experimentally verified protein-protein interactions mined from the
scientific literature by expert curators. The curated data can be analyzed in the
context of the high throughput data and viewed graphically with the 'MINT Viewer'

Website:

http://mint.bio.uniroma2.it/mint/Welcome.do

Name:

Human Protein Reference Database

Comment:

The Human Protein Reference Database represents a centralized platform to visually
depict and integrate information pertaining to domain architecture, post-translational
modifications, interaction networks and disease association for each protein in the
human proteome

The NCI's Cancer Genome Anatomy Project sought to determine the gene expression profiles
of normal, precancer, and cancer cells, leading eventually to improved detection,
diagnosis, and treatment for the patient. Resources generated by the CGAP initiative
are available to the broad cancer community

The UniProtKB-GOA project aims to provide high-quality Gene Ontology (GO) annotations
to proteins in the UniProt Knowledgebase (UniProtKB) and International Protein Index
(IPI) and is a central dataset for other major multi-species databases; such as Ensembl
and NCBI

OptiTope aims at assisting immunologists in designing epitope-based vaccines. It is
an easy-to-use tool to determine a provably optimal set of epitopes with respect to
overall immunogenicity in a specific individual or a target population, free of charge

Provides a large database of publicly available sequence and annotation data along
with an integrated tool set for examining and comparing the genomes of organisms,
aligning sequence to genomes, and displaying and sharing users' own annotation data

SYFPEITHI is a database comprising more than 7,000 peptide sequences known to bind
class I and class II MHC molecules. The entries are compiled from published reports
only

Website:

http://www.syfpeithi.de/

Name:

Melanoma Molecular Map Project

Comment:

MMMP Databases, putting together the pieces of the melanoma puzzle. Seven interconnected
databanks for the interactive collection, update and consultation of the translational
and clinical information on melanoma biology and treatment.

10. Tools for the Bench and Other Useful Websites

A. Primer Design Software

Examples

Name:

Primer3

Comment:

Primer3 is a free online tool to design and analyze primers for PCR and real time
PCR experiments. Primer3 can also select single primers for sequencing reactions and
can design oligonucelotide hybridization probes

MethPrimer is a program for designing bisulfite-conversion-based methylation PCR Primers.
It can design primers for Methylation-Specific PCR (MSP), Bisulfite-Sequencing PCR
(BSP) and Bisulfite-Restriction PCR

Sfold predicts RNA duplex thermodynamics for rational siRNA design. It supports target
accessibility prediction and rational design of antisense oligonucleotides (ASO) and
nucleic acid probes. It can design an ASO for a gene of interest based on the mRNA
sequence

To use the cellular systems biology approach to improve patient stratification for
clinical trial enrollments. Cellumen is collaborating with the Mayo Clinic and Foundation
to create panels of cellular biomarkers using multiplexed fluorescence to apply to
patient cells and tissues, starting with breast cancer

Microsoft Word Add-In for the GenePattern Reproducible Research Document (GRRD)

Comment:

To facilitate publishing reproducible results, GenePattern automatically captures
the history of any computational work being done, allowing scientists to easily generate
pipelines to reproduce computational methods

H. Nanotechnology

Examples

Name:

Inno.CNT

Comment:

The Inno.CNT website gives an updated and wide overview of the research status of
carbon nanotubes as one of the most promising nanomaterial to open up completely new
dimensions in biomedical applications

Conclusion

Immune biomarkers are playing an increasingly important role in the successful development,
clinical evaluation, and immune monitoring of cancer immunotherapies. The references,
products and online resources in this Cancer Immunotherapy Biomarkers Resource Document
were identified by the authors and the SITC/iSBTc Taskforce on Immunotherapy Biomarkers
to support the discovery, evaluation and application of biomarkers for cancer immunotherapy.
These selected references and links serve as a compass to point investigators to useful
resources in this ever growing, and important field of cancer immunotherapy biomarkers.
Emerging issues surrounding cancer immunotherapy biomarker discovery and clinical
application will continue to be addressed in upcoming SITC Annual Meetings and Associated
Programs [13].

Competing interests

DB, JB, EW, MLD, CMB, LGD, ST, TFG, LHB and FFM declare that they have no competing
interests. BAF is co-founder of UbiVac, LLC and serves on the scientific advisory
boards of Micromet, Inc. and MannKind Corporation.

Davide Bedognetti is a participant in the NIH Graduate Partnership Program and a graduate
student at University of Genoa. Davide Bedognetti's fellowship is supported by the
Conquer Cancer Foundation of the American Society of Clinical Oncology (2011 Young
Investigator Award).